ArticleInvestigational new drugs2021
Screening and identification of potential biomarkers and therapeutic drugs in melanoma via integrated bioinformatics analysis.
Article in Investigational new drugs, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Review
- CDH3-AS1 antisense RNA enhances P-cadherin translation and acts as a tumor suppressor in melanoma.Cell reports · 2025Article
- From mechanisms to therapies: the multifaceted roles of guanylate-binding protein 2 in immunity, cancer, and beyond.Frontiers in immunology · 2025Review
- Guanylate binding protein 5 accelerates gastric cancer progression via theAmerican journal of cancer research · 2023Article
- Tissue-derived extracellular vesicles in cancers and non-cancer diseases: Present and future.Journal of extracellular vesicles · 2021Review
- Anti-malarial drug dihydroartemisinin downregulates the expression levels ofOncology letters · 2021Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Melanoma is a highly aggressive malignant skin tumor with a high rate of metastasis and mortality. In this study, a comprehensive bioinformatics analysis was used to clarify the hub genes and potential drugs. Download the GSE3189, GSE22301, and GSE35388 microarray datasets from the Gene Expression Omnibus (GEO), which contains a total of 33 normal samples and 67 melanoma samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) approach analyze DEGs based on the DAVID. Use STRING to construct protein-protein interaction network, and use MCODE and cytoHubba plug-ins in Cytoscape to perform module analysis and identified hub genes. Use Gene Expression Profile Interactive Analysis (GEPIA) to assess the prognosis of genes in tumors. Finally, use the Drug-Gene Interaction Database (DGIdb) to screen targeted drugs related to hub genes. A total of 140 overlapping DEGs were identified from the three microarray datasets, including 59 up-regulated DEGs and 81 down-regulated DEGs. GO enrichment analysis showed that these DEGs are mainly involved in the biological process such as positive regulation of gene expression, positive regulation of cell proliferation, positive regulation of MAP kinase activity, cell migration, and negative regulation of the apoptotic process. The cellular components are concentrated in the membrane, dendritic spine, the perinuclear region of cytoplasm, extracellular exosome, and membrane raft. Molecular functions include protein homodimerization activity, calmodulin-binding, transcription factor binding, protein binding, and cytoskeletal protein binding. KEGG pathway analysis shows that these DEGs are mainly related to protein digestion and absorption, PPAR signaling pathway, signaling pathways regulating stem cells' pluripotency, and Retinol metabolism. The 23 most closely related DEGs were identified from the PPI network and combined with the GEPIA prognostic analysis, CDH3, ESRP1, FGF2, GBP2, KCNN4, KIT, SEMA4D, and ZEB1 were selected as hub genes, which are considered to be associated with poor prognosis of melanoma closely related. Besides, ten related drugs that may have therapeutic effects on melanoma were also screened. These newly discovered genes and drugs provide new ideas for further research on melanoma.
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